Data Engineer

6650 Rue Saint-Urbain, Montréal, QC H2S 3G9, Canada

Full-time

Company Description

IVADO Labs is an AI-powered startup located in Montreal at the heart of one of the fastest growing AI community in the world. We work to identify and solve the most complex and highest value business problems that can be addressed through data science techniques. To achieve this, we provide data science, operations research and artificial intelligence solutions and software products to a broad range of industry and technology partners.

Job Description

We are currently looking for a Data Engineer.

In this role, you will work in a client project environment with an AI-Agile Team composed of a Product Manager, consultant, Delivery Team Lead and Data Scientist and contribute to the translation of complex AI/data science algorithms into scalable software. Core duties are:

Design, code, create tests, and integrate new features and functionality

Design, build, and productize complex data pipelines

Learn the different AI/data science components/models in order for the algorithm to be properly translated in production code

Apply CI/CD practices to prevent integration problems as well as ensure that the code is releasable at any point in time

Participate in the estimation of the Stories based on defined Acceptance Criteria and Definition of Done

Some of the technologies we are using and are looking for:

Cloud: AWS, Azure or GCP

Languages:Python, Java, C++, SCALA and Javascript (nice to have)

Big Data:Hadoop, Spark, Hive

Relational Database:MySql, postgres SQL, Oracle, MS-SQL

NoSql: Cassandra, Elastic search, Mongo DB

Qualifications

You have 3+ year experience in building B2B solutions in a cloud environment (must have)

You have experience with Operations Research / Machine Learning / Deep Learning (asset)

You have experience in Big Data (Hadoop, Spark, Hive) (asset)

You are a strong full stack developer, fluent in one or more of the prominent tools/platforms and able to implement end-to-end solutions

You have previous exposure to AI/data science concepts and, with the guidance of seasoned AI/data science engineers, are proficient in the translation of those concepts into production-grade, efficient code (asset).